181 resultados para DC Distribution System


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With an increasing number of small-scale renewable generator installations, distribution network planners are faced with new technical challenges (intermittent load flows, network imbalances…). Then again, these decentralized generators (DGs) present opportunities regarding savings on network infrastructure if installed at strategic locations. How can we consider both of these aspects when building decision tools for planning future distribution networks? This paper presents a simulation framework which combines two modeling techniques: agent-based modeling (ABM) and particle swarm optimization (PSO). ABM is used to represent the different system units of the network accurately and dynamically, simulating over short time-periods. PSO is then used to find the most economical configuration of DGs over longer periods of time. The infrastructure of the framework is introduced, presenting the two modeling techniques and their integration. A case study of Townsville, Australia, is then used to illustrate the platform implementation and the outputs of a simulation.

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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

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Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pairwise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighboring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools.

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This paper focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the active power and the DC capacitor voltage control of the Doubly Fed Induction Generator (DFIG) based wind generator. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings of the DFIG system is also investigated. The results of the time domain simulation studies are presented to elucidate the effectiveness of the TS-fuzzy controller compared with conventional PI controller in the DFIG system. The proposed TS-fuzzy controller can improve the fault ride through capability of DFIG compared to the conventional PI controller

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Recent advances in the planning and delivery of radiotherapy treatments have resulted in improvements in the accuracy and precision with which therapeutic radiation can be administered. As the complexity of the treatments increases it becomes more difficult to predict the dose distribution in the patient accurately. Monte Carlo methods have the potential to improve the accuracy of the dose calculations and are increasingly being recognised as the “gold standard” for predicting dose deposition in the patient. In this study, software has been developed that enables the transfer of treatment plan information from the treatment planning system to a Monte Carlo dose calculation engine. A database of commissioned linear accelerator models (Elekta Precise and Varian 2100CD at various energies) has been developed using the EGSnrc/BEAMnrc Monte Carlo suite. Planned beam descriptions and CT images can be exported from the treatment planning system using the DICOM framework. The information in these files is combined with an appropriate linear accelerator model to allow the accurate calculation of the radiation field incident on a modelled patient geometry. The Monte Carlo dose calculation results are combined according to the monitor units specified in the exported plan. The result is a 3D dose distribution that could be used to verify treatment planning system calculations. The software, MCDTK (Monte Carlo Dicom ToolKit), has been developed in the Java programming language and produces BEAMnrc and DOSXYZnrc input files, ready for submission on a high-performance computing cluster. The code has been tested with the Eclipse (Varian Medical Systems), Oncentra MasterPlan (Nucletron B.V.) and Pinnacle3 (Philips Medical Systems) planning systems. In this study the software was validated against measurements in homogenous and heterogeneous phantoms. Monte Carlo models are commissioned through comparison with quality assurance measurements made using a large square field incident on a homogenous volume of water. This study aims to provide a valuable confirmation that Monte Carlo calculations match experimental measurements for complex fields and heterogeneous media.

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Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key-chain), to each sensor node. If a pair of nodes does not have a common key after deployment then they must find a key-path with secured links. The objective is to minimize the keychain size while (i) maximizing pairwise key sharing probability and resilience, and (ii) minimizing average key-path length. This paper presents a deterministic key distribution scheme based on Expander Graphs. It shows how to map the parameters (e.g., degree, expansion, and diameter) of a Ramanujan Expander Graph to the desired properties of a key distribution scheme for a physical network topology.

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A novel intelligent online demand side management system is proposed for peak load management in low-voltage distribution networks. This method uses low-cost controllers with low-bandwidth two-way communication installed in custumers’ premises and at distribution transformers to manage the peak load while maximising customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by simulation of three different feeder types.

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Advances in technology introduce new application areas for sensor networks. Foreseeable wide deployment of mission critical sensor networks creates concerns on security issues. Security of large scale densely deployed and infrastructure less wireless networks of resource limited sensor nodes requires efficient key distribution and management mechanisms. We consider distributed and hierarchical wireless sensor networks where unicast, multicast and broadcast type of communications can take place. We evaluate deterministic, probabilistic and hybrid type of key pre-distribution and dynamic key generation algorithms for distributing pair-wise, group-wise and network-wise keys.

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Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pair wise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighbouring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighbouring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools. Comparison to probabilistic schemes shows that our combinatorial approach produces better connectivity with smaller key-chain sizes.

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Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

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Most existing research on maintenance optimisation for multi-component systems only considers the lifetime distribution of the components. When the condition-based maintenance (CBM) strategy is adopted for multi-component systems, the strategy structure becomes complex due to the large number of component states and their combinations. Consequently, some predetermined maintenance strategy structures are often assumed before the maintenance optimisation of a multi-component system in a CBM context. Developing these predetermined strategy structure needs expert experience and the optimality of these strategies is often not proofed. This paper proposed a maintenance optimisation method that does not require any predetermined strategy structure for a two-component series system. The proposed method is developed based on the semi-Markov decision process (SMDP). A simulation study shows that the proposed method can identify the optimal maintenance strategy adaptively for different maintenance costs and parameters of degradation processes. The optimal maintenance strategy structure is also investigated in the simulation study, which provides reference for further research in maintenance optimisation of multi-component systems.

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As the world’s population is growing, so is the demand for agricultural products. However, natural nitrogen (N) fixation and phosphorus (P) availability cannot sustain the rising agricultural production, thus, the application of N and P fertilisers as additional nutrient sources is common. It is those anthropogenic activities that can contribute high amounts of organic and inorganic nutrients to both surface and groundwaters resulting in degradation of water quality and a possible reduction of aquatic life. In addition, runoff and sewage from urban and residential areas can contain high amounts of inorganic and organic nutrients which may also affect water quality. For example, blooms of the cyanobacterium Lyngbya majuscula along the coastline of southeast Queensland are an indicator of at least short term decreases of water quality. Although Australian catchments, including those with intensive forms of land use, show in general a low export of nutrients compared to North American and European catchments, certain land use practices may still have a detrimental effect on the coastal environment. Numerous studies are reported on nutrient cycling and associated processes on a catchment scale in the Northern Hemisphere. Comparable studies in Australia, in particular in subtropical regions are, however, limited and there is a paucity in the data, in particular for inorganic and organic forms of nitrogen and phosphorus; these nutrients are important limiting factors in surface waters to promote algal blooms. Therefore, the monitoring of N and P and understanding the sources and pathways of these nutrients within a catchment is important in coastal zone management. Although Australia is the driest continent, in subtropical regions such as southeast Queensland, rainfall patterns have a significant effect on runoff and thus the nutrient cycle at a catchment scale. Increasingly, these rainfall patterns are becoming variable. The monitoring of these climatic conditions and the hydrological response of agricultural catchments is therefore also important to reduce the anthropogenic effects on surface and groundwater quality. This study consists of an integrated hydrological–hydrochemical approach that assesses N and P in an environment with multiple land uses. The main aim is to determine the nutrient cycle within a representative coastal catchment in southeast Queensland, the Elimbah Creek catchment. In particular, the investigation confirms the influence associated with forestry and agriculture on N and P forms, sources, distribution and fate in the surface and groundwaters of this subtropical setting. In addition, the study determines whether N and P are subject to transport into the adjacent estuary and thus into the marine environment; also considered is the effect of local topography, soils and geology on N and P sources and distribution. The thesis is structured on four components individually reported. The first paper determines the controls of catchment settings and processes on stream water, riverbank sediment, and shallow groundwater N and P concentrations, in particular during the extended dry conditions that were encountered during the study. Temporal and spatial factors such as seasonal changes, soil character, land use and catchment morphology are considered as well as their effect on controls over distributions of N and P in surface waters and associated groundwater. A total number of 30 surface and 13 shallow groundwater sampling sites were established throughout the catchment to represent dominant soil types and the land use upstream of each sampling location. Sampling comprises five rounds and was conducted over one year between October 2008 and November 2009. Surface water and groundwater samples were analysed for all major dissolved inorganic forms of N and for total N. Phosphorus was determined in the form of dissolved reactive P (predominantly orthophosphate) and total P. In addition, extracts of stream bank sediments and soil grab samples were analysed for these N and P species. Findings show that major storm events, in particular after long periods of drought conditions, are the driving force of N cycling. This is expressed by higher inorganic N concentrations in the agricultural subcatchment compared to the forested subcatchment. Nitrate N is the dominant inorganic form of N in both the surface and groundwaters and values are significantly higher in the groundwaters. Concentrations in the surface water range from 0.03 to 0.34 mg N L..1; organic N concentrations are considerably higher (average range: 0.33 to 0.85 mg N L..1), in particular in the forested subcatchment. Average NO3-N in the groundwater has a range of 0.39 to 2.08 mg N L..1, and organic N averages between 0.07 and 0.3 mg N L..1. The stream bank sediments are dominated by organic N (range: 0.53 to 0.65 mg N L..1), and the dominant inorganic form of N is NH4-N with values ranging between 0.38 and 0.41 mg N L..1. Topography and soils, however, were not to have a significant effect on N and P concentrations in waters. Detectable phosphorus in the surface and groundwaters of the catchment is limited to several locations typically in the proximity of areas with intensive animal use; in soil and sediments, P is negligible. In the second paper, the stable isotopes of N (14N/15N) and H2O (16O/18O and 2H/H) in surface and groundwaters are used to identify sources of dissolved inorganic and organic N in these waters, and to determine their pathways within the catchment; specific emphasis is placed on the relation of forestry and agriculture. Forestry is predominantly concentrated in the northern subcatchment (Beerburrum Creek) while agriculture is mainly found in the southern subcatchment (Six Mile Creek). Results show that agriculture (horticulture, crops, grazing) is the main source of inorganic N in the surface waters of the agricultural subcatchment, and their isotopic signature shows a close link to evaporation processes that may occur during water storage in farm dams that are used for irrigation. Groundwaters are subject to denitrification processes that may result in reduced dissolved inorganic N concentrations. Soil organic matter delivers most of the inorganic N to the surface water in the forested subcatchment. Here, precipitation and subsequently runoff is the main source of the surface waters. Groundwater in this area is affected by agricultural processes. The findings also show that the catchment can attenuate the effects of anthropogenic land use on surface water quality. Riparian strips of natural remnant vegetation, commonly 50 to 100 m in width, act as buffer zones along the drainage lines in the catchment and remove inorganic N from the soil water before it enters the creek. These riparian buffer zones are common in most agricultural catchments of southeast Queensland and are indicated to reduce the impact of agriculture on stream water quality and subsequently on the estuary and marine environments. This reduction is expressed by a significant decrease in DIN concentrations from 1.6 mg N L..1 to 0.09 mg N L..1, and a decrease in the �15N signatures from upstream surface water locations downstream to the outlet of the agricultural subcatchment. Further testing is, however, necessary to confirm these processes. Most importantly, the amount of N that is transported to the adjacent estuary is shown to be negligible. The third and fourth components of the thesis use a hydrological catchment model approach to determine the water balance of the Elimbah Creek catchment. The model is then used to simulate the effects of land use on the water balance and nutrient loads of the study area. The tool that is used is the internationally widely applied Soil and Water Assessment Tool (SWAT). Knowledge about the water cycle of a catchment is imperative in nutrient studies as processes such as rainfall, surface runoff, soil infiltration and routing of water through the drainage system are the driving forces of the catchment nutrient cycle. Long-term information about discharge volumes of the creeks and rivers do, however, not exist for a number of agricultural catchments in southeast Queensland, and such information is necessary to calibrate and validate numerical models. Therefore, a two-step modelling approach was used to calibrate and validate parameters values from a near-by gauged reference catchment as starting values for the ungauged Elimbah Creek catchment. Transposing monthly calibrated and validated parameter values from the reference catchment to the ungauged catchment significantly improved model performance showing that the hydrological model of the catchment of interest is a strong predictor of the water water balance. The model efficiency coefficient EF shows that 94% of the simulated discharge matches the observed flow whereas only 54% of the observed streamflow was simulated by the SWAT model prior to using the validated values from the reference catchment. In addition, the hydrological model confirmed that total surface runoff contributes the majority of flow to the surface water in the catchment (65%). Only a small proportion of the water in the creek is contributed by total base-flow (35%). This finding supports the results of the stable isotopes 16O/18O and 2H/H, which show the main source of water in the creeks is either from local precipitation or irrigation waters delivered by surface runoff; a contribution from the groundwater (baseflow) to the creeks could not be identified using 16O/18O and 2H/H. In addition, the SWAT model calculated that around 68% of the rainfall occurring in the catchment is lost through evapotranspiration reflecting the prevailing long-term drought conditions that were observed prior and during the study. Stream discharge from the forested subcatchment was an order of magnitude lower than discharge from the agricultural Six Mile Creek subcatchment. A change in land use from forestry to agriculture did not significantly change the catchment water balance, however, nutrient loads increased considerably. Conversely, a simulated change from agriculture to forestry resulted in a significant decrease of nitrogen loads. The findings of the thesis and the approach used are shown to be of value to catchment water quality monitoring on a wider scale, in particular the implications of mixed land use on nutrient forms, distributions and concentrations. The study confirms that in the tropics and subtropics the water balance is affected by extended dry periods and seasonal rainfall with intensive storm events. In particular, the comprehensive data set of inorganic and organic N and P forms in the surface and groundwaters of this subtropical setting acquired during the one year sampling program may be used in similar catchment hydrological studies where these detailed information is missing. Also, the study concludes that riparian buffer zones along the catchment drainage system attenuate the transport of nitrogen from agricultural sources in the surface water. Concentrations of N decreased from upstream to downstream locations and were negligible at the outlet of the catchment.

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Introduction: The motivation for developing megavoltage (and kilovoltage) cone beam CT (MV CBCT) capabilities in the radiotherapy treatment room was primarily based on the need to improve patient set-up accuracy. There has recently been an interest in using the cone beam CT data for treatment planning. Accurate treatment planning, however, requires knowledge of the electron density of the tissues receiving radiation in order to calculate dose distributions. This is obtained from CT, utilising a conversion between CT number and electron density of various tissues. The use of MV CBCT has particular advantages compared to treatment planning with kilovoltage CT in the presence of high atomic number materials and requires the conversion of pixel values from the image sets to electron density. Therefore, a study was undertaken to characterise the pixel value to electron density relationship for the Siemens MV CBCT system, MVision, and determine the effect, if any, of differing the number of monitor units used for acquisition. If a significant difference with number of monitor units was seen then pixel value to ED conversions may be required for each of the clinical settings. The calibration of the MV CT images for electron density offers the possibility for a daily recalculation of the dose distribution and the introduction of new adaptive radiotherapy treatment strategies. Methods: A Gammex Electron Density CT Phantom was imaged with the MVCB CT system. The pixel value for each of the sixteen inserts, which ranged from 0.292 to 1.707 relative electron density to the background solid water, was determined by taking the mean value from within a region of interest centred on the insert, over 5 slices within the centre of the phantom. These results were averaged and plotted against the relative electron densities of each insert with a linear least squares fit was preformed. This procedure was performed for images acquired with 5, 8, 15 and 60 monitor units. Results: The linear relationship between MVCT pixel value and ED was demonstrated for all monitor unit settings and over a range of electron densities. The number of monitor units utilised was found to have no significant impact on this relationship. Discussion: It was found that the number of MU utilised does not significantly alter the pixel value obtained for different ED materials. However, to ensure the most accurate and reproducible MV to ED calibration, one MU setting should be chosen and used routinely. To ensure accuracy for the clinical situation this MU setting should correspond to that which is used clinically. If more than one MU setting is used clinically then an average of the CT values acquired with different numbers of MU could be utilized without loss in accuracy. Conclusions: No significant differences have been shown between the pixel value to ED conversion for the Siemens MV CT cone beam unit with change in monitor units. Thus as single conversion curve could be utilised for MV CT treatment planning. To fully utilise MV CT imaging for radiotherapy treatment planning further work will be undertaken to ensure all corrections have been made and dose calculations verified. These dose calculations may be either for treatment planning purposes or for reconstructing the delivered dose distribution from transit dosimetry measurements made using electronic portal imaging devices. This will potentially allow the cumulative dose distribution to be determined through the patient’s multi-fraction treatment and adaptive treatment strategies developed to optimize the tumour response.

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The dc capacitors voltage unbalancing is the main technical drawback of a diode-clamped multilevel inverter (DCMLI), with more than three levels. A voltage-balancing circuit based on buck–boost chopper connected to the dc link of DCMLI is a reliable and robust solution to this problem. This study presents four different schemes for controlling the chopper circuit to achieve the capacitor voltages equalisation. These can be broadly categorised as single-pulse, multi-pulse and hysteresis band current control schemes. The single-pulse scheme does not involve faster switching actions but need the chopper devices to be rated for higher current. The chopper devices current rating can be kept limited by using the multi-pulse scheme but it involves faster switching actions and slower response. The hysteresis band current control scheme offers faster dynamics, lower current rating of the chopper devices and can nullify the initial voltage imbalance as well. However, it involves much faster switching actions which may not be feasible for some of its applications. Therefore depending on the system requirements and ratings, one of these schemes may be used. The performance and validity of the proposed schemes are confirmed through both simulation and experimental investigations on a prototype five-level diode-clamped inverter.

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The composition of a series of hydroxycarbonate precursors to copper/zinc oxide methanol synthesis catalysts prepared under conditions reported as optimum for catalytic activity has been studied. Techniques employed included thermogravimetry (TG), temperature-programmed decomposition (TPD), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), and Raman and FTIR spectroscopies. Evidence was obtained for various structural phases including hydrozincite, copper hydrozincite, aurichalcite, zincian malachite and malachite (the concentrations of which depended upon the exact Cu/Zn ratio used). Significantly, previously reported phases such as gerhardite and rosasite were not identified when catalysts were synthesized at optimum solution pH and temperature values, and after appropriate aging periods. Calcination of the hydroxycarbonate precursors resulted in the formation of catalysts containing an intimate mixture of copper and zinc oxides. Temperature-programmed reduction (TPR) revealed that a number of discrete copper oxide species were present in the catalyst, the precise concentrations of which were determined to be related to the structure of the catalyst precursor. Copper hydrozincite decomposed to give zinc oxide particles decorated by highly dispersed, small copper oxide species. Aurichalcite appeared to result ultimately in the most intimately mixed catalyst structure whereas zincian malachite decomposed to produce larger copper oxide and zinc oxide grains. The reason for the stabilization of small copper oxide and zinc oxide clusters by aurichalcite was investigated by using carefully selected calcination temperatures. It was concluded that the unique formation of an 'anion-modified' oxide resulting from the initial decomposition stage of aurichalcite was responsible for the 'binding' of copper species to zinc moieties.